Assessment of Quality of Life in Outpatients With Advanced Cancer: The Accuracy of Clinician Estimations and the Relevance of Spiritual Well-Being—A Hoosier Oncology Group Study
Bibliographic record
Abstract
PURPOSE: To evaluate the association between quality-of-life (QOL) impairment as reported by patients and QOL impairment as judged by nurses or physicians, with and without consideration of spiritual well-being (SWB). PATIENTS AND METHODS: A total of 163 patients with advanced cancer were enrolled onto a therapeutic trial, and cross-sectional data were derived from clinical and demographic questionnaires obtained at baseline, including assessment of patient QOL and SWB. Clinicians rated the QOL impairment of their patients as mild, moderate, or severe. Clinician-estimated QOL impairment and patient-derived QOL categories were compared. Correlation coefficients were estimated to associate QOL scores using different instruments. The analysis of variance method was used to compare Functional Assessment of Cancer Therapy-General scores on categorical variables. RESULTS: There was no significant association between self-assessment scores and marital status, education level, performance status, or predicted life expectancy. However, a strong relationship between SWB and QOL was noted (P <.0001). Clinician-estimated QOL impairment matched the level of patient-derived QOL correctly in approximately 60% of cases, with only slight variation depending on the method of categorizing patient-derived QOL scores. The accuracy of clinician estimates was not associated with the level of SWB. Interestingly, a subset analysis of the inaccurate estimates revealed an association between lower SWB and clinician underestimation of QOL impairment (P =.0025). CONCLUSION: Clinician estimates of QOL impairment were accurate in more than 60% of patients. SWB is strongly associated with QOL, but it is not associated with the overall accuracy of clinicians' judgments about QOL impairment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".